

Highlight 1
The use of an advanced LLM allows users to achieve a high level of accuracy in filtering out unwanted content.
Highlight 2
Users can tweak the system prompt for filtering, providing a personalized experience that suits their needs.
Highlight 3
The integration with Groq's API ensures that the content analysis is performed quickly, resulting in minimal delays in the user experience.

Improvement 1
Improve the onboarding process with clearer instructions on how to set up and use the filtering options effectively.
Improvement 2
Explore ways to extend functionality to other social media platforms beyond Twitter to increase user engagement.
Improvement 3
Implement a feedback system where users can report ineffective filters or suggest improvements, enhancing the system continuously.
Product Functionality
Consider adding pre-set filtering options for common unwanted content types to simplify user selection.
UI & UX
Enhance the user interface to make it more intuitive, possibly by including visual aids or tutorials to guide new users.
SEO or Marketing
Create informative content, such as blog posts or videos, that explains the benefits of using Unbaited and how it works, to attract more users.
MultiLanguage Support
Implement multi-language support to cater to a global audience, making the extension accessible to non-English speakers.
- 1
How does Unbaited filter my Twitter feed?
Unbaited uses a Large Language Model (LLM) to analyze and filter tweets based on a customizable system prompt that targets engagement bait and political content.
- 2
Do I need to pay for the Groq API key?
No, you can obtain a free API key from Groq, which is necessary for the extension to function.
- 3
Can I use Unbaited on any browser?
Currently, Unbaited is available as a Chrome extension, so it can only be used on Google Chrome.